Global diurnal precipitation cycle in the AI model GraphCast and a 5‐km unified model: challenges and opportunities

Gentile, E. S. ORCID: https://orcid.org/0000-0002-6878-5145, Hunt, K. M. R. ORCID: https://orcid.org/0000-0003-1480-3755, Tomassini, L. ORCID: https://orcid.org/0000-0003-3361-7384, Harvey, B. ORCID: https://orcid.org/0000-0002-6510-8181 and Martinez-Alvarado, O. ORCID: https://orcid.org/0000-0002-5285-0379 (2026) Global diurnal precipitation cycle in the AI model GraphCast and a 5‐km unified model: challenges and opportunities. Geophysical Research Letters, 53 (9). e2025GL120961. ISSN 1944-8007 doi: 10.1029/2025GL120961

Abstract/Summary

This study evaluates the ability of the AI weather forecast model GraphCast to reproduce the global diurnal cycle of boreal summer precipitation, comparing it with Integrated Multi-satellite Retrievals for GPM (IMERG) satellite observations, the ERA5 reanalysis, and an experimental global 5-km Met Office Unified Model (UM) which is convection permitting but still retains an active scale-aware parametrization. ERA5 captures large-scale rainfall patterns but exhibits a premature afternoon peak and excessively weak nocturnal precipitation over land compared to IMERG. GraphCast, while reproducing realistic mean spatial rainfall distributions, inherits, and amplifies these timing and amplitude biases, concentrating precipitation near-midday and producing very little nocturnal signal. The 5-km UM improves nocturnal precipitation across many regions but overestimates rainfall over oceans and initiates convection too early over land, likely due to the still active convective parametrization. Our analysis shows that these contrasting behaviors highlight both challenges and opportunities for improving precipitation prediction through hybrid AI-physics approaches.

Item Type	Article
URI	https://centaur.reading.ac.uk/id/eprint/129678
Identification Number/DOI	10.1029/2025GL120961
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > NCAS Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	American Geophysical Union
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